code: def _trackable_children(self, save_type="checkpoint", **kwargs):
      if save_type == "savedmodel":
          # SavedModel needs to ignore the execution functions.
          train_function = getattr(self, "train_function", None)
          test_function = getattr(self, "test_function", None)
          predict_function = getattr(self, "predict_function", None)
          self.train_function = None
          self.test_function = None
          self.predict_function = None
  
      children = super()._trackable_children(save_type, **kwargs)
  
      if save_type == "savedmodel":
          self.train_function = train_function
          self.test_function = test_function
          self.predict_function = predict_function
  
          for tracked_attr in self._tracked:
              tracked_item = getattr(self, tracked_attr)
              if isinstance(tracked_item, tracking.TrackedList):
                  children[tracked_attr] = list(tracked_item)
              if isinstance(tracked_item, tracking.TrackedDict):
                  children[tracked_attr] = dict(tracked_item)
              if isinstance(tracked_item, tracking.TrackedSet):
                  children[tracked_attr] = list(tracked_item)
  
      return children
  
file_path: keras/keras/backend/tensorflow/layer.py
imports: import tensorflow
  from keras.backend.tensorflow.trackable import KerasAutoTrackable
  from keras.utils import tf_utils
  from keras.utils import tracking
label_desc: Use image node_id 3 for calling the TFLayer obj's underlying member method code with example usage: obj._trackable_children(save_type) and returns: children